The task is to estimate approach time (time-to-go (TTG)) of non-ballistic threats (e.g. missiles) using passive infrared imagery captured from a sensor on the target platform (e.g. a helicopter). The threat information available in a frame of data is angular position and signal amplitude.
A Kalman filter approach is presented that is applied to example amplitude data to estimate TTG. Angular information alone is not sufficient to allow analysis of missile guidance dynamics to provide a TTG estimate. Detection of the launch is required as is additional information in the form of a terrain database to determine initial range. Parameters that relate to missile dynamics might include proportional navigation constant and motor thrust. Differences between actual angular position observations and modelled values can beused to form an estimator for the parameter set and thence to the TTG.
The question posed here is, "how can signal amplitude information be employed to establish observability in a state-estimation-based model of the angular data to improve TTG estimate performance without any other source of range information?"
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